This study was conducted to examining the socio-cultural impact of the COVID-19 pandemic that swept the world around 2020, and the transformation of norms and social problems due to COVID-19. For this, the characteristics of changes in the socio-cultural norms of the 14th century European Black Death, a representative example of the pandemic, were derived, and based on this, the COVID-19 pandemic was analyzed. The Black Death served as an opportunity to change social norms based on the existing religious authority and the power of the feudal system to the Enlightenment. The population declination and labor shortage also promoted commercialization and mechanization. Printing, which spread during this period, led to the popularization of knowledge, which raised the level of thinking and led to epochal scientific development. This became the foundation of the Industrial Revolution. Like the recent Black Death, COVID-19 has triggered changes in social norms. The technological environment of metaverse, a mixture of virtual and reality, has changed the norm of a consistent identity into free and open identities exerting various potentials through alternate characters. In addition, meme, which are about people being friendly to those with the same worldview as him on the metaverse, weakened the sense of isolation in non-face-to-face situations. Artificial intelligence (AI), which developed during the COVID-19 pandemic, has entered the stage of being used for creative activities beyond the function of assisting humans. Discussions were held on what new social problems would be created by the social norms changed due to the COVID-19 pandemic.
We analyze the perceptions and requirements of early childhood teachers for artificial intelligence(AI) education to develop an AI education program for 5-year-olds. As for the research methodology, we conducted a survey and an in-depth interview to extract the AI educational elements centering on the analysis stage, the first stage of the ADDIE model. The research result is that first, it is necessary to design a curriculum that combines the contents of early childhood education and AI education to be naturally accepted as AI education for 5-year-olds. Second, an evaluation tool for AI education that can showcase the teacher's reflection should be developed systematically. Third, it is necessary to support a play-centered AI education support and environment for early childhood teachers. Lastly, it is essential to establish a system that can be continuously operated in the field of early childhood education in consideration of AI education in the non-curricular curriculum. It is expected that in the future, a play-oriented AI education program for 5-year-olds will be developed to spread awareness of AI education for infants and present an AI education approach for each age and stage of learners.
The Journal of Korea Institute of Information, Electronics, and Communication Technology
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v.15
no.2
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pp.178-188
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2022
The introduction of virtual power plants is actively being discussed to solve the problem of grid acceptability caused by the spread of distributed renewable energy, which is the key to achieving carbon neutrality. However, a new business such as virtual power plants is difficult to secure economic feasibility at the initial stage of introduction because it is common that there is no compensation mechanism. Therefore, appropriate support including subsidy is required at the early stage. But, it is generally difficult to obtain the cost model to determine the subsidy level because of the lack of enough data for the new business model. In this study, a survey of domestic experts on the requirements, appropriate scale, and cost required for the introduction of virtual power plants is conducted. First, resource composition scenarios are designed from the survey results to consider the impact of the resource composition on the cost. Then, the cost estimation model is obtained using the individual cost estimation data for their resource compositions using logistic regression analysis. In the case study, appropriate initial subsidy levels are analyzed and compared for the virtual power plants on the scale of 20-500MW. The results show that mid-to-large resource composition cases show 29-51% lower cost than small-to-large resource composition cases.
Illegal gambling through online gambling sites has become a significant social problem. The development of Internet technology and the spread of smartphones have led to the proliferation of illegal gambling sites, so now illegal online gambling has become accessible to anyone. In order to mitigate its negative effect, the Korean government is trying to detect illegal gambling sites by using self-monitoring agents or reporting systems such as 'Nuricops.' However, it is difficult to detect all illegal sites due to limitations such as a lack of staffing. Accordingly, several scholars have proposed intelligent illegal gambling site detection techniques. Xu et al. (2019) found that fake or illegal websites generally have unique features in the HTML tag structure. It implies that the HTML tag structure can be important for detecting illegal sites. However, prior studies to improve the model's performance by utilizing the HTML tag structure in the illegal site detection model are rare. Against this background, our study aimed to improve the model's performance by utilizing the HTML tag structure and proposes Tag2Vec, a modified version of Doc2Vec, as a methodology to vectorize the HTML tag structure properly. To validate the proposed model, we perform the empirical analysis using a data set consisting of the list of harmful sites from 'The Cheat' and normal sites through Google search. As a result, it was confirmed that the Tag2Vec-based detection model proposed in this study showed better classification accuracy, recall, and F1_Score than the URL-based detection model-a comparative model. The proposed model of this study is expected to be effectively utilized to improve the health of our society through intelligent technology.
With the global pandemic in the era of the 4th industrial revolution, the business environment of companies was engulfed by rapid volatility and uncertainty. In particular, in order for an organization to have high competitiveness due to the spread of the flexible work system, relationship management with members of the organization and self-directed job crafting are recognized as important key resources. This study aims to investigate how relational energy and resilience within a corporate organization affect job crafting and to verify the effect of job crafting on individual job performance. For empirical research, 400 valid responses to employees of general companies were analyzed by SPSS 26.0 and Smart PLS 3.0. As a result of the analysis, first, it was confirmed that relational energy did not have a positive (+) effect on task crafting. Second, it was found that relational energy had a positive (+) effect on relational crafting and cognitive crafting, respectively. Third, it was found that resilience had a positive (+) effect on both task crafting, relationship crafting, and cognitive crafting that constitute job crafting. Fourth, it was found that job crafting had a positive (+) effect on individual job performance. Based on these research results, we intend to derive academic and practical implications and provide practical help to follow-up researchers and stakeholders.
With the increase in the spread of smart devices and the impact of COVID-19, the consumption of media contents through smart devices has significantly increased. Along with this trend, the amount of media contents viewed through OTT platforms is increasing, that makes contents recommendations on these platforms more important. Previous contents-based recommendation researches have mostly utilized metadata that describes the characteristics of the contents, with a shortage of researches that utilize the contents' own descriptive metadata. In this paper, various text data including titles and synopses that describe the contents were used to recommend similar contents. KLUE-RoBERTa-large, a Korean language model with excellent performance, was used to train the model on the text data. A dataset of over 20,000 contents metadata including titles, synopses, composite genres, directors, actors, and hash tags information was used as training data. To enter the various text features into the language model, the features were concatenated using special tokens that indicate each feature. The test set was designed to promote the relative and objective nature of the model's similarity classification ability by using the three contents comparison method and applying multiple inspections to label the test set. Genres classification and hash tag classification prediction tasks were used to fine-tune the embeddings for the contents meta text data. As a result, the hash tag classification model showed an accuracy of over 90% based on the similarity test set, which was more than 9% better than the baseline language model. Through hash tag classification training, it was found that the language model's ability to classify similar contents was improved, which demonstrated the value of using a language model for the contents-based filtering.
Yon Ha Chung; So Dam Kim;Hyun Jeong Seo;Hojun Lee;Tae Jung Song
Journal of the Society of Disaster Information
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v.18
no.4
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pp.861-872
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2022
The purpose of this study was to establish a complex disaster scenario that can comprehensively consider various disaster situations that may occur in the utility tunnel. Method: In order to comprehensively consider the correlation between disasters, a composite disaster scenario was derived from a combination of damage factors, respectively. A risk assessment was performed in order to derive the priorities of the scenarios. And based on the results, the priorities of complex disaster scenarios were set. Result: Based on the disaster cases in the utility tunnel, a plan was prepared for complex disaster scenarios centered on damage. A complex disaster scenario was specified using a semi-quantitative evaluation method for single and multiple disaster factors such as fire, flooding, and earthquake. Conclusion: The composite disaster scenario derived from this study can be used for the prevention and preparation of damage when the precursor symptoms of a disaster are detected. In addition, the results of this study are expected to be used as basic data for preparing strategic plans and preparing complex disaster response technologies to induce rapid response and recovery in case of emergency disasters.
Ju Hyoun Wang;Jung Soo Han;Jun Kil Choi;Hwang Goo Lee
Korean Journal of Environmental Biology
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v.41
no.2
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pp.101-108
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2023
Recently, in relation to climate change, many studies have been conducted to predict the potential habitat area and distribution range of tilapia and the suitability of habitat for each species. Most tilapia are tropical fish that cannot survive at water temperatures below 10 to 12℃, although some tilapia can survive at 6 to 8℃. This study predicted habitable areas and the possibility of spreading of habitat ranges of tilapia (Oreochromis niloticus and Oreochromis aureus) known to inhabit domestic streams. Due to climate change, it was found that habitats in the Geum River, Mangyeong River, Dongjin River, Seomjin River, Taehwa River, Hyeongsan River, and the flowing in East Sea were possible by 2050. In addition, it was confirmed that tilapia could inhabit the preferred lentic ecosystem such as Tamjin Lake, Naju Lake, Juam Lake, Sangsa Lake, Jinyang Lake, Junam Reservoir, and Hoedong Reservoir. In particular, in the case of tilapia, which lives in tributaries of the Geumho River, Dalseo Stream, and the Nakdong River, its range of habitat is expected to expand to the middle and lower of the Nakdong River system. Therefore, it is judged that it is necessary to prepare physical and institutional management measures to prevent the spread of the local population where tilapia currently inhabits and to prevent introduction to new habitats.
'Woori Philosophy' is the modern philosophy of Korea. The purpose of this study is to make a hypothetical model of the methodologies used in Woori Philosophy, to analyze and classify this system of thought as it appears in the Jeon-gyeong (『典經』), to confirm the effectiveness of the model's application, and to present the model's methodological best practices. In this paper, I have made a standard for Woori Philosophy by combining existing studies. Thereby, although it is preliminary, I have presented the model as a way of achieving Woori philosophy by analysis and division of this thought in the Jeon-gyeong. As a result, the Jeongyeong's content is organized into an order in frequency which emerges as Model②, Model①, Essential Model, Model④, and Model③. These models can be evaluated to show that the Jeon-gyeong progressively inherited different schools of traditional Korean thought, while simultaneously characterizing them as Korean in many areas, never ignored the problems of the times or an awareness of the world, and furthermore, did not senselessly or blindly accept foreign objects spread into Korea from 1880~1890. Therefore, the Jeon-gyeong shows a comprehensive methodology for the implementation of Woori philosophy based on its own historical setting. It can be evaluated as the best practices which took many ideas and made those ideas its own. Through this, I was able to confirm its effectiveness as a methodology of Woori Philosophy and was able to extract its best practices. However, the ideas in the Jeon-gyeong did not directly become Woori Philosophy. To solve our problems in the 21st century, there is still an assignment to interpret these ideas through the application of this model. If the existing research on Daesoon Thought (大巡思想) is to become Woori Philosophy, then it should do so through the application of this model.
Sinjungsin Mask Play, one of Ttangseolbeop, is related to Seongjusin's life story. Sinjungsin Mask Play is a reconstruction of the story of the folk gods Seongjusin met while returning home. Seongjusin's life story proceeds in the form of Mask Play, and the monk who leads the sermon plays narration and main roles. Many believers play various roles and musicians. Sinjungsin Mask Play introduces many folk beliefs, sounds for intrigue, and talks. Sinjungsin Mask Play uses the same method of enumeration and repetition as the existing Mask Play. The repetition of a sentence or phrase plays a role in foreseeing the meaning of the context or foretelling the development of the plot to the audience. This repetition is intended to emphasize the situation of the scene and to create rhythm. Since Mask Play was exclusively for the common people, Mask Play actors use the repeating method commonly used in folk songs to form lines. This gives the audience a familiarity, effectively communicating the lines and responding to their tastes. Sinjungsin Mask Play borrowed people's way of playing for the public's mission. It inherits the dramatic forms of traditional traditional plays such as repetition of words or sentences or phrases, codification of words or sentences, borrowing of existing songs, and formal expression units. In addition, through repeated performances, believers can easily and easily learn and understand. This is the dramatic form and characteristics of Sinjungsin Mask Play. Sinjungsin Mask Play was handed down from Faith Communities and was used as a means of folk cultivation to spread illegality. Buddhism externalizes the process of accepting folk beliefs through Mask Play, and in the case of Shinto who participated directly or indirectly, they naturally acquire the belief system of Hwaeom Kyung through play. Sinjungsin Mask Play, one of Ttangseolbeop, can be said to have great value as an ICH, as well as popularization and mission.
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